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Behavioural Economic Perspectiveson Inertia in Travel Decision Making
Job van Exel
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Behavioural Economic Perspectives
on Inertia in Travel Decision Making
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commissie: prof.dr. J.C.J.M. van den Bergh
prof.dr. K.A. Brookhuis
prof.dr. W.F. van Raaij
prof.dr. G.P. van Wee
prof.dr. H.J. van Zuylen
ISBN: 978-90-5335-488-9
Job van Exel, 2011
Cover: 99 most important words (using www.wordle.net)
Printed by Ridderprint on FSC certified paper
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VRIJE UNIVERSITEIT
Behavioural Economic Perspectives on Inertia in Travel Decision Making
ACADEMISCH PROEFSCHRIFT
ter verkrijging van de graad Doctor aan
de Vrije Universiteit Amsterdam,
op gezag van de rector magnificus
prof.dr. L.M. Bouter,
in het openbaar te verdedigen
ten overstaan van de promotiecommissie
van de faculteit der Economische Wetenschappen en Bedrijfskunde
op dinsdag 20 december 2011 om 15.45 uur
in de aula van de universiteit,
De Boelelaan 1105
door
Nicolaas Jacob Arnold van Exel
geboren te Amsterdam
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promotor: prof.dr. P. Rietveld
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Preface
Een proefschrift schrijf je in je eentje, maar niet alleen. Ik dank in het
bijzonder mijn ouders Didi en Niek, mijn zussen Anna, Ines, Irene en
Lydia, mijn thuis Anke, Fleur, Bregje en Sofie, T. Ad, mijn vrienden Gjalt,
KJ, Michiel, Rob, Wagi en Werner, en mijn aanhoudend scherpe en
geduldige promotor Piet Rietveld. Maar zeker ook alle overige familie,
vrienden, collegas bij NEI en iBMG, en medestanders in de straat, op hetplein, langs de lijn, en in het werk- en belangenveld die door de jaren
heen belangstelling en betrokkenheid hebben getoond. Dankzij -en soms
ondanks- jullie is dit proefschrift nu volbracht!
Ter nagedachtenis van grootmoeder, opa en Jaap
voor hun onuitwisbare indruk.
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Contents
1 Introduction..............................................................................11.1 What is a behavioural economic perspective? 31.2 What is inert behaviour? 81.3 Objectives and outline of this thesis 9
2 Travel behaviour on the move?..................................................112.1 What has been the approach to individual behaviour in transportation
research? 112.1.1 Travel is a derived demand 112.1.2 Travel choice is hierarchical 142.1.3 Observed travel behaviour is the result of rational choice 172.1.4 People differ in preferences, strength of habit and choice set 21
2.2 What is rational behaviour according to mainstream economics? 282.3 Which alternative approaches are proposed in behavioural economics? 38
2.3.1 Bounded rationality 392.3.2 Prospect theory 522.3.3Judgement of probabilities 562.3.4 Interdependence 592.3.5Adaptive and relative preferences 622.3.6 Intertemporal choice 67
2.4 Outlook to the following chapters 71
3 Public transport strikes and traveller behaviour ............................733.1 Introduction 733.2 Review of previous studies 753.3 The 1999 rail strike in the Netherlands 893.4 Discussion and conclusion 92
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4 Anticipated and actual behavioural reactions to a rail strike ...........954.1 Introduction 954.2
Methods and data 98
4.3 Results 1014.4 Discussion and conclusion 110
5 Could you also have made this trip by another mode?................. 1135.1 Introduction 1135.2
Methods and data 116
5.3 Results 1205.4 Discussion and conclusion 129
6 Travel time perceptions and travel choice.................................. 1336.1 Introduction 1336.2
Methods and data 135
6.3 Results 1386.4 Discussion and conclusion 142
7 I can do perfectly well without a car!...................................... 1497.1 Introduction 1497.2 Methods and data 1517.3 Results 1597.4 Discussion and conclusion 171
8 Discussion and conclusion ....................................................... 177
List of tables................................................................................ 193
List of figures............................................................................... 195
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List of references.......................................................................... 197
Summary .................................................................................... 235
Samenvatting .............................................................................. 241
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Introduction
1
Introduction
Why is it so difficult to persuade car drivers to use public transport more
often? is probably one of the most discussed questions among transport
researchers and policy makers. Despite many policy initiatives aimed at
making alternative modes of transportation more attractive, car use has
steadily increased during the past decades, in absolute as well as in
relative terms. Each second person in the European Union (EU) now owns
a car and about 85% of all passenger kilometres are made by car
(Eurostat 2009). Considering the substantial differences in car ownership
and use between EU Member States and with the US, this trend may be
expected to persist.
The increase in car ownership and use has generated traffic congestion
and has made travel time reliability an issue of concern among road users
and transport policy makers. Particularly in the more densely urbanised
areas congestion has become a common and persistent phenomenon1,
leading to frustrated personal mobility expectations, substantial problems
in the accessibility of important economic and social centres and concerns
over the viability of town centres. Next to these economic effects of roadcongestion, reducing car use has also become a focus of concern from the
starting point of global and local environmental changes, and health and
safety effects (Goodwin 1995).
1 In 2005 the Netherlands celebrated50 years of traffic-jams. Over this period, trafficcongestion grew to 35,000 traffic jams per year with a total length of 115 thousandkilometres and a total time loss of 50 million hours. The average time loss on a trip of 30
kilometres with free flow travel time of 18 minutes amounts to 2 minutes and mayincrease to 12 minutes during peak hours. About 40% of this time loss is structural andpredictable, 30% is structural and non-predictable and 30% is incidental and non-predictable. Direct costs of time loss were estimated at 900 million per year, total costsat 3 billion or 0.5% of GDP (KiM 2010; MoT 2004a; 2004b).
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Chapter 1
2
Various reasons have been put forward for the increasing dominance of
the car. For instance, during the second half of last century the real prices
of travelling by car and public transport hardly changed, while during thissame period the quality of travelling by car (including system quality)
increased substantially relative to that of public transport (MoT 1991). A
number of socio-economic and cultural trends during this period were
associated with a rise in car ownership and use, among them increasing
welfare (Jekel 2011; KiM 2010; Dargay et al. 2007; Cameron et al. 2004;
Dargay 2001; Figure 1.1), and many countries, among them the
Netherlands, responded with policies that were chiefly concerned with
accommodating increasing demand for road capacity (SCP 2003; 1993;
MoT 1997) possibly not the optimal response from a societal perspective
(Litman 2007).
Figure 1.1 Income and car ownership 2
2 Source: Transport Statistics Report: International Comparison of Transport Statistics1970- 1994. London: Department of Transport, 1997.
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Introduction
3
While most car users may favour investments in the public transport
system, they typically cannot be encouraged to use public transport more
than occasionally, if at all. As Banister (2002) phrased it, the car isgenerally believed to be the most desirable form of transport and will
normally be used as the preferred form of transport, no matter how
attractive the alternative might be. The user can always think of a reason
why the car is necessary for that particular journey. But why is it that car
drivers who clearly understand and experience the downsides of travelling
by car are so persistent in their choice for the car?
Although prominent, mode choice is only one example of individual travel
choices that are sometimes difficult to explain for transportation
researchers and policy makers. The aim of this thesis is to advance our
understanding of individual travel behaviour by exploring this inertia from
a behavioural economic perspective.
1.1 What is a behavioural economic perspective?Non-economists generally identify the economic perspective on behaviour
with homo economicus, the rational self-interested utility maximizer.
Normative mainstream economists will tend to agree: economics is about
agents behaving rationally in order to maximise their individual utility.
Homo economicus (or economic man) is usually dated back to Adam
Smith (1776), and is the toolbox generations of economists left university
with. Hence, if as Bagozzi (1992) suggested longevity is taken as a
measure of success of a theory, homo economicus undoubtedly has been
successful. Nonetheless, for almost as long, this behavioural foundation of
mainstream economic theory has been contested for its descriptive
accuracy (McFadden 1999; Hennipman 1945).
In the course of the 20th century both the popularity and controversiality
of homo economicus have developed alongside the increasing focus in
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Chapter 1
4
economics on mathematical expression and modelling. The single
objective for behaviour and the restrictive situational circumstances
presumed in the mainstream economic approach have proven to beconvenient for modelling all sorts of behaviour and such models have
predicted many behaviours quite accurately. Sen (1998) however argued
that this mathematical exactness of formulation proceeds hand in hand
with remarkable inexactness of content; the world is made to fit this
momentous assumption, rather than the assumption being made to fit the
world. The analytical discipline that confines itself to such constricted
behavioral regularity is, by now, very extensively developed, with many
technical achievements to its credit. This has tended to make the limiting
assumption seem robust and natural. The analytical tools and the tradition
of exacting and rigorous analysis associated with formal economics also
militate against departures that may appear to be mushy and soft. Most
people, however, are not natural born economists (Cipriani, Lubian & Zago
2009). Rubinstein (2006) and Klamer (1987), among others, expressed
the concern that, following these achievements, present-day economists
learn how mathematical models work but no longer learn to reflect on why
these models work and which factors are filtered out because they are not
easily formalised and quantified, but may nevertheless be significant for
understanding individual behaviour. If economists who use these
equations and diagrams would read the original surrounding texts, Thaler
(1997) posed, they would find that the classic economists were well aware
of the influence of psychological factors such as self-control and fashion
on behaviour, often left out of modern economic analyses. Morgan (2006)
describes the varying characterizations of economic man since introduced
by Adam Smith (1776). And already about a century ago, Clark (1918)
stated that economists may attempt to ignore these other, psychological
factors that may influence peoples behaviour, but that if economics poses
to be a science of human behaviour this inevitably involves psychological
assumptions, whether these are explicit or not. The popularity of homo
economicus in the different subject areas where economic analysis has
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Introduction
5
been applied in the past even seems to be associated with the prevalence
and relevance of such other factors: for instance, self-interested utility
maximisation appears more commonly accepted as a behavioural model intransport and labour economics and less in environmental and health
economics.
During the last decades a wide body of literature emerged accentuating
anomalies that the mainstream economic approach has difficulties
accounting for, pointing out that homo economicus may constitute not
more than a partial account of behaviour. Tomer (2001) argued thatdifferent heterodox schools of thought were formed in the last decades in
reaction to this accumulating evidence, as groupings of economists who
share common objections to economic man and who share a common
view regarding what aspects of man should be emphasised to rectify the
problems associated with mainstream economists use of economic man.
The various stripes of economics analysis, depicting alternative theories of
individual behaviour, are commonly grouped under the label behavioural
economics. Although there is no undisputed definition or domain of
behavioural economics, contemporary textbooks most resemble a
common playground of economists, social psychologists and increasingly
also scholars from other domains involved in the study of human nature
and behaviour. Handgraaf and van Raaij (2005) described behavioural
economics as a growing common perspective between economists and
psychologists, based on mutual interest and increasing interaction
between scholars from both disciplines, which meanwhile is leading to a
separate perspective with converging language and methodological
approaches. Loewenstein (1999) defined a behavioural economist as a
methodological eclectic, an economist who brings insights from other
disciplines to bear on economic phenomena. The Society for the
Advancement of Behavioral Economics (SABE) gave the following
description in the announcement of its 2003 conference: Behavioral
economics is an umbrella that encompasses a wide variety of research
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Chapter 1
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agendas that either extend or deviate from the traditional, neoclassical
economics paradigm. By relaxing assumptions such as perfect foresight,
unchanging preferences, costless optimisation, and market equilibrium,contributions in behavioral economics offer explanations for economic
phenomena that depend upon how people behave. Psychological and
sociological issues are often pertinent, making behavioral economics
significantly interdisciplinary. These alternative assumptions and
approaches taken together provide a behavioural economic perspective on
behaviour.
Mainstream economists have not paid much attention to the attacks and
achievements of behavioural economists during the last decades and have
mainly pursued their own research agenda. Divergent ideas about how
people do behave are considered of limited relevance for economics as a
normative science and disregarded because individual utility maximisation
is viewed as superior to concepts from other disciplines for the analysis of
behaviour (Folmer & Lindenberg 2011; Folmer 2007; Bovenberg & van de
Klundert 1999; Lea, Tarpy & Webley 1987; van Witteloostuijn 1988;
1991). This indicates that there is not a single, unified economic
perspective on individual behaviour, but that different schools of thought
coexist, with divergent approaches to the analysis of behaviour.3,4
According to Van Raaij (1995) and Loewenstein (1992), the distaste for
psychology became widespread among economists in the first decades of
the twentieth century, when they sought to stake out the independence of
economics as a science. While Commons (1934), for instance, still argued
3 Roth (1996) discerned four main theories of behaviour operant within contemporaryeconomics at large: (i) Bernoullis (1738) risk neutral economic man, choosing betweenoutcomes with a known probability function; (ii) Von Neumann and Morgensterns (1953)expected utility maximising man, making choice under uncertainty; (iii) Kahneman andTverskys (1979) almost rational economic man, choosing between uncertain prospects;and (iv) psychological man, acting according to a collection of mental processes elicited
by different descriptions of options, frames, contexts, and choice procedures.
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Introduction
7
that human behaviour is basically goal oriented and purposive but at the
same time heavily influenced by stupidity, ignorance, and passion, the
psychological richness that characterised economics in the late 19
th
andthe early 20th century (e.g. Pech & Milan 2009) was soon replaced by
mathematical and graphical analysis that seemed to render psychology
superfluous. A renewed interest in psychology originated in the 1970s and
80s, evident from the establishment of the Journal of Behavioural
Economics in the early 70s -later continued as the Journal of Socio-
Economics- and the Journal of Economic Psychology in the early 80s (van
Raaij 1981). The International Association for Research in Economic
Psychology (IAREP) and the Society for the Advancement of Behavioral
Economics (SABE) were also established in the early 80s.
At the beginning of the new millennium, alternative behavioural
assumptions again came to the centre of scientific economic interest when
The Royal Swedish Academy of Sciences awarded the 2002 Nobel Prize in
economics to Vernon Smith and Daniel Kahneman; the first for laying the
foundation to the field of experimental economics, the latter for
integrating insights from psychology into economics and demonstrating
how human decisions under uncertainty systematically depart from
predictions by mainstream economic theory (together with the late Amos
Tversky; see van Raaij 1998). In the aftermath, a handful of scholarly
handbooks and numerous popular books were published, popular
magazines like The Economist spent generous attention to the subject,
and very recently the Dutch Scientific Council for Government Policy made
choice behaviour one of their topics for reconnaissance (WRR 2009;
Tiemeijer 2011; 2009). This thesis is rooted in this renewed interest in
alternative assumptions and approaches for the economic analysis of
individual behaviour.
4 Socio-economics (Etzioni 2008; 2003; 1998) and institutional economics (Commons1931; Hodgson 1998; Williamson 2000) could be regarded as main schools next to
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1.2 What is inert behaviour?Inert behaviour (or inertia) is generally aligned with common terms from
literature such as invariant, constant, stable, steady, and settled
behaviour. In mainstream economic literature inertia thus defined is
viewed as an anomaly, an unanticipated stickiness of behaviour, and
sometimes referred to as less rational, nonrational, irrational or even
foolish behaviour (e.g. McFadden 1999; Janis & Mann 1977). Literature
provides a variety of characterisations of inertia that share a notion of
invariance. According to Assael (1992), inert behaviour may becharacterised by passive beliefs, low involvement, and little information
processing. The decision maker only seeks some acceptable level of
satisfaction. He does not care very much about the object of choice, e.g.
because it is not closely related to the decision makers personality and
lifestyle characteristics or group norms and values. Decision making is
associated with low motivation and little deliberation. If at all, decision is
evaluated afterwards. More concise characterisations from economic and
transportation literature include: whenever possible, consume exactly
what was consumed in the past (Becker 1978); resistance to change
(Ansoff 1987); carrying on as before (Sutton 1994); the effect of gaining
experience or getting familiar in previous periods on current choice
(Cherchi & Manca 2011; Train 2009; Cantillo, de Dios Ortzar, Williams
2007); a relatively simple decision making process in order to save time
and effort as a result of low involvement (van Kesteren & Meertens 1999);
falling back on past behaviour (Heijs 1999); thresholds that need to be
crossed before changing routine behaviour, factors which encourage
keeping the status quo (Bovy & Stern 1990); thoughtlessly sticking to a
chosen alternative until a bad experience or other major change occurs
(Windervanck & Tertoolen 1998).
mainstream, neoclassical economics and behavioural economics, although the boundariesbetween the non-mainstream approaches are not unambiguously defined.
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Introduction
9
Here inertia is defined as invariant behaviour while from a mainstream
economic perspective change of behaviour is deemed rational. The
opposite of course is also possible; this is not discussed separately as theantecedents are expected to be similar (Janis & Mann 1977). In the
context of travel behaviour inertia implies that people sometimes tend to
stick to a particular travel pattern even though switching to an alternative
pattern appears to be utility maximising for the individual.
1.3 Objectives and outline of this thesisThe aim of this thesis is to advance our understanding of individual travel
behaviour by exploring possible causes for inertia from a behavioural
economic perspective, and to investigate further some specific ideas
emerging from behavioural economics in the context of inert travel
behaviour.
Chapter 2 starts with an outline of how individual behaviour is generally
treated in transportation research, followed by a discussion of homo
economicus and the assumptions and circumstances under which it is
regarded a satisfactory descriptive model of individual behaviour by
mainstream economists. Then, an overview is given of alternative
behavioural assumptions that have been proposed to explain the main
anomalies economists have observed using homo economicus as a
starting point and some examples from transportation research are
discussed. All these departures from the mainstream economic approach
will be discussed under the heading behavioural economics, as
denominated by prominent scholars in the field (e.g. Thaler 1997; Tomer
2001).
Chapters 3 to 7 discuss the results of further investigations of a number of
ideas from behavioural economics in the context of inert travel behaviour.
Chapter 3 addresses the effect of a strike on the travel behaviour of public
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transport users. Strikes are an interesting context for studying travel
behaviour, because travellers preferred alternative is removed from their
travel choice set and they are forced to reconsider their travelopportunities. We review available studies of strikes in the public transport
sector and present the results of a survey carried out after a short,
unannounced railway strike in the Netherlands. Chapter 4 continues on
this subject and compares anticipated and actual behavioural reactions to
a pre-announced strike of Dutch national railways. We use longitudinal
data collected days before and after the strike to compare stated and
actual travel choices, considering peoples travel choice sets. Chapter 5
investigates the accurateness of car drivers perceptions of public
transport travel time and their potential effect on the consideration of
public transport as an alternative mode of transportation. Chapter 6
discusses perceived travel possibilities of car and train travellers and
associations with characteristics of the traveller and the trip. Chapter 7,
finally, explores car and public transport travellers preferences for
middle-distance travel. Differences and similarities in motivation for
travel, liking of travel modes, and levels of involvement and cognitive
effort applied in travel decision making are used to uncover preference
segments. The potential for inertia among travellers with these
preferences is discussed.
Chapter 8 discusses the implications of the findings in this thesis for travel
behaviour research and policy and concludes.
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Travel behaviour on the move
11
Travel behaviour on the move?
This chapter aims to explore possible causes for inert travel behaviour
from a behavioural economic perspective, where inertia is defined as
invariant behaviour while from a mainstream economic perspective
change of behaviour appears to be rational. Section 2.1 starts with an
overview of how individual behaviour has generally been approached in
transportation research. Section 2.2 follows with an account of the basic
assumptions underlying the mainstream economic approach to behaviour
and highlights the central arguments of advocates and critics of this
approach. Section 2.3 discusses alternative approaches that have been
proposed in contemporary behavioural economic literature and gives some
examples of applications from transportation literature. Section 2.4 gives
an outline of how a selected number of causes for inertia will be further
investigated in the following chapters.
2.1 What has been the approach to individual behaviour intransportation research?
2.1.1 Travel is a derived demandA basic premise in transportation research is that travel demand is derived
from the need or desire to participate in activities spread over space and
time, despite the fact that travel may sometimes also have an intrinsic
process utility and be valued for its own sake (Basmajian 2010;
Mokhtarian et al. 2001). About half of the growth in mobility in the
Netherlands between 1970 and 2000 resulted from increased individual
mobility associated with socioeconomic and cultural trends towards more
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Chapter 2
12
individualized and intensified lifestyles (SCP 2003; 1993; MoT 1997). This
individualisation process was associated with an increase in female labour
market participation, a reduction in household size, a larger share of two-
earner households5, a shift to more out-of-home activities and,
subsequently, to an increasing number of people combining in-home and
out-of-home responsibilities. Intensifying activity patterns were a
consequence of higher activity participation and activity diversification,
leading to higher time pressure and a higher need to combine activities
efficiently. In addition, trends in the labour market like the shift towardservice industries, higher specialisation and flexible working hours have
led to a greater geographical dispersion in activity patterns and lower
interconnectivity of time schedules.6 In a way the same is true for the
leisure market, where increasing differentiation and specialisation has lead
to a grater propensity to travel to search out niche markets and visit
special interest events (Mackellar 2006). Thus, as a consequence of more
individualised and intensified lifestyles, people have engaged in more
activities at different space-bound locations, for shorter periods of time,
leading to higher levels of mobility and need for flexibility, and therefore
to a higher dependence on individual modes of transport, predominantly
the car. About 80% of the growth in car use in the Netherlands in the
period between 1985 and 2008 was associated with increased individual
mobility, resulting from people travelling more often and farther both forcommuting and leisure purpose (KiM 2010; 2007; RVW 2010; Jekel
2011). These trends obviously are not specific to the Netherlands,
although this growth in mobility and the resulting congestion has made
that the average commuting time in the Netherlands is longer than in any
5 Leading to additional spatial dependencies in the choice of home and work locations(Maat & Timmermans 2009; Rich 2001; van Wee 1994).6
For instance, only 3% of the Dutch work force lives close enough to walk to work (meandistance 1 km; mean travel time 7 min) and 5% to cycle (4 km; 14 min). Main reasonsfor not moving residence: nice living environment, social attachment, and use ofcommuting time as private time, for dealing with stress, and for switching between workand home mindsets (www.cbs.nl).
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Travel behaviour on the move
13
other European country (OECD 2010). Most western countries have
experienced similar changes in household structure and lifestyles during
the past decades, resulting in a growth of mobility, car ownership and car
dependence (e.g., Banister & Marshall 2000; Cameron et al. 2004;
Mackellar 2006; Stopher & Lee-Gosselin 1997). Lyons et al. (2000) argued
that these mobility trends will pose new policy challenges. The proportion
of repetitive trips -in terms of regularity and fixed temporal and spatial
orientation- will decline and that of discretionary trips will rise, increasing
the dependency on individual modes of transport and the inertia topolicies aimed at a modal shift toward collective modes of transport.
These issues have been studied extensively in the 1980s and 90s.
Van Wee (1994; 1997) analysed the interaction between the choice of
location of space bound activities and travel resistances, (perceptions of)
the travel costs and time to cover the distance between two space bound
activities. As for many households housing and work are the most spacebound activities and commuting is the most frequent trip, the latter was
expected to play a substantial role in decisions to move home or change
job. Van Wee (1997) however found that the decision to leave the current
home or the selection of a new one was affected by a range of
interdependent factors7, but that accessibility by car or public transport
played only a minor role. Raux and Andan (1997) reported similar
results.8 Tillema, van Wee and Ettema (2010) found that in residential
7 For instance, household members needs and desires regarding housing and activities,the supply and relative importance to the household of services at specific locations, theirsatisfaction with activities and their location, and the familys lifecycle, budget,commitments (e.g., investments, personal careers and activity patterns) andattachments (e.g., to persons, neighbourhoods).8 They analysed household migration decisions and found eight motives for mobility. Twowere internal (or autonomous, controlled) i.e., based on household preferences and a
deliberate search process- and six were external (or dependent, imposed) i.e., based onexternal pressure or advice and reactive to market opportunities that come across. Thelarge majority (83%) of migrations was dominated by financial constraints, lack ofinformation and the pressure of the housing market, only a minority of households (17%)was in full control of their own migration.
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Chapter 2
14
location choices people are more sensitive to travel and housing costs
than to travel time, and more to travel costs than to housing costs.
Windervanck and Tertoolen (1998) argued that commuters evaluate travel
alternatives once, after they change home or work location, but
subsequently stick to the chosen alternative thoughtlessly, until a bad
experience or some major change occurs in the transport system or in
their personal lives. For instance, van Ommeren (2000) found commuting
time to be an appropriate measure of search effort for a new housing or
work location. Moreover, studies have observed that households find their
travel behaviour subject to fairly similar, predictable pressures and
constraints related to their lifecycle stage (Maat & Timmermans 2009;
Dargay 2004; Jones et al. 1983; Clarke & Dix 1983). Despite the
emergence of new forms and more flexible scheduling of activity
participation following the increasing adoption of information and
communication technologies (Alexander, Dijst & Ettema 2010), asignificant proportion of all travel still has a few fixed destinations as core
stops (e.g., work, school, shops, gym) and these serve as anchors for
much of the other household members travel behaviour (Hanson & Huff
1988). Day-to-day travel choices thus appear to be subordinated to
longer-term mobility related choices. For understanding and predicting
travel behaviour it is then important to acknowledge and consider the
sequential and conditional decisions travellers make.
2.1.2 Travel choice is hierarchicalThe findings discussed before imply that travel behaviour is embedded in
prior mobility related choices and strongly influenced by longer-term
decisions and commitments such as residential and employment location
and car ownership (Fischer 1993; Ben-Akiva & Lerman 1985; Domencich& McFadden 1975). This hierarchical choice structure means that day-to-
day travel choices about destination, departure time, travel mode and
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Travel behaviour on the move
15
route for trips are made given the prevailing opportunities and constraints
in the travel choice set and that the likelihood a travel alternative will be
considered may depend on prior choices and considerations at least as
much as on present motivations and constraints (Raney et al. 2000;
Louvire & Street 2000). In other words, for understanding and predicting
travel behaviour it becomes relevant to distinguish between choice set
formation and actual choice given the prevailing choice set (Fischer 1993;
Ben-Akiva & Lerman 1985; Domencich & McFadden 1975). Travel choice
sets have been advanced as one of the main reasons for the gap betweenobserved and rational travel behaviour, making the predictions of
transport models relying on this assumption less accurate and the
transport policies based on them less effective (Raney et al. 2000;
Mokhtarian & Salomon 1997). When analysing travel choices it is thus
important to distinguish between travellers with different choice sets and
to explain why choice sets differ (Wardman & Tyler 2000; Fischer 1993).
Travel choice set formation may be influenced by a variety of factors, such
as the supply of travel alternatives, geographic and socio-economic
circumstances, individual preferences and perceptions of characteristics of
travel alternatives, past travel experience, and habituation (e.g., Kingham
et al. 2001, Wardman & Tyler 2000; SCP 2000; van Wee 1997; Rooijers &
Welles 1996; Fotheringham & OKelly 1989; Ben-Akiva & Lerman 1985;
Burnett & Hanson 1982; McFadden 1981). In addition, there is a
difference between objective and subjective choice sets (Burnett & Hanson
1982; Punj & Brookes 2001). A persons objective choice set (or
opportunity set) is determined by the location of activities, the travel
alternatives theoretically available (i.e., road infrastructure, public
transport provision, transport policy and fiscal regulations), and the
persons capabilities to walk, cycle, use public transport and drive a car. Apersons subjective choice set (or consideration set) concerns the set of
alternatives the person is aware of and considers viable and acceptable.
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For instance, the choice set of a captive traveller may consist of a single
mode, perhaps even in combination with a mandatory route or departure
time. This may represent either objective or subjective lack of choice.
However, if at all, the subjective choice set is the one actively considered
in the choice process.
Some studies have investigated objective and subjective choice sets more
in depth. Brg et al. (1977) studied travel opportunities in a sample of
people living in a densely populated area well served by public transport
and found that although almost 60% of car users had a public transport
alternative for the trip they were making, 85% of them had not
considered using public transport because of its perceived suitability, lack
of information, attitude towards public transport and preference for
travelling by car. In a follow-up study, Brg and Erl (1983) found that half
of a sample of car drivers had the objective opportunity to use public
transport for the trip they were making, but that only five percentperceived to have a real choice between car and public transport (Figure
2.1a). In addition, they found that not more than half of the non-captive
car users would switch to public transport following increases in petrol
prices of up to 200%. Most car drivers indicated they would rather cancel
their trip than switch to public transport. Kropman and Katteler (1990)
replicated this study and found that 83% of a sample of morning peak car
drivers had the objective possibility to switch to public transport for the
trip they were making, but that only 17% actually perceived to have
freedom of choice as a result of various constraints on their travel
behaviour (Figure 2.1b).9
9 Perceived freedom to switch to public transport varied with gender (women 36% / men
14%), age (
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Figure 2.1 Hierarchical identification of car drivers with opportunity to use publictransport 10
2.1.3 Observed travel behaviour is the result of rational choiceWith its roots in engineering and geography, the development of ideas in
travel behaviour research generally has been in terms of econometric
models, largely working under the assumption that observed travel
behaviour is the result of rational choice; the field has been
predominantly entrenched in a quantitative paradigm (Clifton & Handy
2003). Three main types of travel behaviour models have been
prominent: (1) four-stage models; (2) disaggregate behavioural models;
and (3) activity-based models (Blauwens, de Baere & van de Voorde
2010; Hensher & King; 2001; Banister 2002; Fischer 1993).
10 Source: (a) adapted from Brg and Erl (1983); (b) adapted from Kropman and Katteler(1990); a + (-) indicates that public transport is (not) a suitable alternative for thecar driver.
100
51 49
1. Objective
optionsyesno
13 36
yes no2. Materialconstraints
9 27
- +
16 11
- +
1 10
- +
2 8
- +
3
5
-
+
3. Information
Car drivers who have the option to use public transport
4. Travel time
5. Costs
6. Service/comfort
7. Subjectively in favour
100
13 83
yesno
44 43
yes no
2 41
- +
2 39
- +
15 24
- +
4 20
- +
3
17
-
+
(a) (b)
1. Objective
options
2. Materialconstraints
3. Costs
Car drivers who have the option to use public transport
4. Access and egressproblems
5. Travel time
6. Time schedule / convenience
7. Subjectively in favour
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The traditional four-stage aggregate transport planning model was
developed in the 1950s and 60s. The aim of the model was to predict
aggregate traffic flows between zones on the basis of empirically
established relationships between travel, land-use and socio-economic
variables, for the purpose of regional and infrastructure network planning.
Travel behaviour was seen as the result of four consecutive rational
choices, which were modelled independently: whether to travel, where to
travel, which mode to use, and what route to follow (e.g., Lee-Gosselin &
Pas 1997; Banister 2002; Fischer 1993).11
Although the separate modelshave been improved considerably since the early days, the theoretical
basis for four-stage models is weak, the analytical framework has proven
to be inflexible and costly, whereas predictions have often been inaccurate
(e.g., Fischer 1993; Banister 2002; De Dios Ortzar & Willumsen 2001).
For instance, studies comparing longer-term travel forecasts with later
observed levels demonstrated that forecast errors would had been no
larger if the transport models had started from the assumption of no
change in the exogenous variables (Jones et al. 1983). The main
theoretical objections concern the sequential structure and absence of
feedback between the stages, the focus on aggregate data, and the lack
of theoretical underpinning (Blauwens, de Baere & van de Voorde 2010).
The four-stage model is entirely empirically based and makes no attempt
at understanding why people travel, the constraints and uncertaintiespeople face, and what happens when travel patterns become routine or
habits are formed.
11 First, a trip generation model estimates the number of trips for different purposes froma certain (urban) zone, based upon characteristics of that zone such as the type and sizeof economic activity and the type, number and income of households. Second, a trip
distribution model determines the destination of trips for each purpose, usually based ongeneralised travel costs minimisation. Third, a modal splitmodel estimates the number oftrips with car and public transport between zones, based on mode choice models. Finally,a route assignmentmodel addresses route-choice for any trip between two zones, basedagain on generalised travel costs minimization.
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The increasing availability of computer hard- and software in the 1970s
and 80s allowed for much more efficient handling of large data sets.
Newly developed disaggregate utility models of travel behaviour turned
the focus to the individual (or the household) rather than zones as the
unit of observation in an attempt to develop models with higher policy
sensitivity (McFadden 2001; Lee-Gosselin & Pas 1997; Banister 2002;
Fischer 1993).12 Disaggregate utility models explain travel behaviour by
relating observed behaviour to characteristics of the individual and the
transport system. These models are based on the mainstream economictheory of rational behaviour and assume that people have full information
and control over all alternatives from the travel opportunity set, are able
to rank these alternatives according to their preferences and to choose the
alternative that maximises their utility, constrained only by time, budget,
the physical environment (Noland & Small 1995; Ben-Akiva & Lerman
1985) and reliability (Noland & Polak 2002; Bates et al. 2001; Bates
2001). Despite their wide application and current level of sophistication
and power (Rietveld & Nijkamp 2003), disaggregate utility models have
been criticised for: (1) their failure to take into account that travel is a
derived demand and the hierarchy between mobility- and travel-related
choices; (2) their focus on modal choice on single trips as separate
events, ignoring linkages in time and space between components of travel
patterns (or trip chains), the interrelations between travel behaviour ofpersons in a household, and the intertemporal dependence between travel
choices; (3) their reliance on unrealistic assumptions about rational
behaviour; and (4) their focus on elegant mathematical model structures
and statistical associations (e.g., Folmer, Oud & Saris 2010; Folmer 2007;
Maat, van Wee & Stead 2005; Lanzendorf 2003; Hensher & King 2001;
Grling & Young 2001; Mehndiratta et al. 2003; Ben-Akiva et al. 1999;
Banister 2002; Fischer 1993; Jones et al. 1983; Burnett & Hanson 1982;
12 See McFadden (2001) for a retrospective on disaggregate travel demand models.
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Heggie 1978); we have outgrown the simplistic notion that the accurate
modelling of human behaviour awaits only sufficient data and computing
power directed to discovering underlying principles analogous to physical
laws (Lee-Gosselin & Pas 1997).13 Later applications have relaxed some
of the assumptions, have attempted to integrate attitudinal factors into
disaggregate utility models and have tested alternative behavioural
assumptions to better explain observed behaviour (Banister 2002; Jones
et al. 1983). These models accommodated concepts such as partial
information and travel time uncertainty (e.g., Hensher & King 2001;Banister 2002), used psychometric scaling techniques to investigate and
quantify subjective variables such as comfort, convenience and reliability
(Lee-Gosselin & Pas 1997) and addressed subgroups with deviating travel
cost structures or preferences (e.g., Larsen & Rekdal 2009; Sohn & Yun
2009).
Activity-based models, which view travel as a part of general patterns ofbehaviour and accommodate notions of the human activity approach
(Jones et al. 1983) and time-space geography (Hgerstrand 1970),
emerged in the mid 1980s. The basic idea is that people undertake
activities in order to satisfy basic needs (e.g., sleeping), personal
preferences (e.g., leisure and lifestyle related activities), role
commitments (e.g., child care and other lifecycle related activities) and
institutional requirements (e.g., school, work). Travel is required to
participate in activities at different points in space and time and therefore
treated as a derived demand (Fischer 1993; Burnett & Hanson 1982;
Jones 1978). So far the complexity of the interactions between all the
constraints (e.g., the linkages between childrens after school activities,
their travel needs and their parents activity-travel patterns; Paleti,
13 Accuracy is lost in various stages of the information chain: perception and reporting ofbehaviour by traveller, administration and interpretation by interviewer, coding ofresponse, modelling and interpretation of results; and this just for the factors underconsideration (Mackett 1983).
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Copperman & Bhat 2011) has inhibited the realization of a comprehensive
theoretical and analytical framework (Clifton & Handy 2003; Goulias 2003;
Fischer 1993). The potential complexity of activity patterns becomes
apparent when one considers how activities may differ in aspects such as
their timing (absolute, or relative to dominant activities such as work),
duration, location, frequency (or repetition), sequencing, importance
(absolute, or relative priority), planning horizon, accessibility of travel
modes, and their degree of specificity (or substitutability) in any of these
aspects (Burnett & Hanson 1982).
Nonetheless, applications of activity-based models have given insight in
the types of constraints that affect peoples travel choices14 and indicate
that activity scheduling considerations may be much more central to day-
to-day travel behaviour than characteristics of travel modes (Lee-Gosselin
& Pas 1997; Banister 2002; Fischer 1993; Goodwin 1983).
2.1.4 People differ in preferences, strength of habit and choice setThe models of travel behaviour discussed above largely rely on travellers
making rational choices, either from the full opportunity set or a
constrained consideration set. Alongside their development and despite
their current level of sophistication, criticism remained about the rational
choice assumption as being unrealistic or lacking descriptive accuracy, and
many argued more attention should be paid to differences in preference
and the influence of habit formation (Anable 2005; Gtz et al. 2003;
Dargay 2001; Raney et al. 2000; Wardman & Tyler 2000; Goodwin 1995;
Burnett & Hanson 1982). That is, as Goodwin (1995) phrased, there is one
14 Travel choice sets lie within a time-space prism shaped by authority, complementarity,capability and coupling constraints. Authority constraints refer to limitations imposed
from outside, such as public transport service areas/timetables. Complementarityconstraints refer to the (im)possibility for activity chaining, such as interoperability andinterconnectivity of transport systems. Capability constraints refer to individuallimitations in time, capacities and means. Coupling constraints refer to interdependenceand need to synchronise joint activities, such as between members of a household.
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simple but important proposition for travel behaviour research and policy
arising from past research: people differ. Travellers should therefore not
be considered as a homogeneous group and policies should not be
directed at the average car driver, but it is important to recognize
distributions of preferences among individuals, understand their
opportunities and constraints and design policies addressing sizeable
subgroups which display a certain kind of behaviour in response to specific
circumstances or changes therein. Wardman and Tyler (2000), for
instance, proposed to distinguish between groups of travellers withdifferent travel choice sets, and Diana and Mokhtarian (2009) according to
the degree of acquaintance with different travel modes.
Various studies have been conducted in the past addressing heterogeneity
in travel behaviour. In the 1980s trip and traveller characteristics were
used to segment travellers into groups with, for instance, homogenous
travel behaviour (Hanson & Huff 1982; 198815
; Huff & Hanson 198616
),according to stage in the family lifecycle (Jones et al. 1983)17 or whether
choice is forced or permissive (Heggie & Jones 1978). In the 1990s
interest shifted to preferences, leading to segments of travellers sharing
15
They argued that travel-activity patterns are organized around a few core stops thatserve as anchors for the rest of activity / location choices and travel behaviour. As anexample, working men and nonworking women demonstrated a high level of repetition intravel-activity behaviour.16 They identified five travel behaviour groups using observed travel characteristics from35-day travel records (e.g., number of trips, trip purpose, proportion single-stop trips).The found that the level of trip making, spatial-extent of the travel-activity pattern andtrip complexity were important discriminators between the five groups, and that the fivegroups had distinct socio-demographic characteristics, in terms of gender, household sizeand establishment density close to home.17 They found stage in family lifecycle to be a useful classificatory variable for identifyingdifferences and regularities in behaviour patterns and underlying decision rules. The
lifecycle groups distinguished included: younger (married) adults without children;families with pre-school children (under 5); families with pre-school children and youngschool children (6-11); families with young school children; families with older schoolchildren (12-15); families of adults, all of working age; older adults, no children in thehousehold; retired persons.
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similar tastes for travel (e.g., Pas & Huber 1992)18 or with different levels
of car dependence (e.g., Kropman & Katteler 1990)19. More recent studies
have focussed on segmentation based on attitude theory. Popuri et al.
(2011) investigated the importance of attitudes in the choice of public
transport to work. They discerned six attitudinal factors20 related to
commuting and found that these contributed considerably to the
explanation of mode choice to work. Shiftan, Outwater and Zhou (2008),
Lieberman et al. (2001) and Proussaloglou et al. (2001) conducted similar
studies.
Anable (2005) identified six travel behaviour segments in terms of
predisposition to use alternatives for car21 and found willingness to switch
to be associated with more favourable attitudes and greater perceived
control over alternative modes, less psychological attachment to the car,
and stronger moral norms. People may thus exhibit similar current travel
behaviour, but may have made this choice in different ways and for
18 They identified five segments of intercity rail travellers (functional traveller, daytripper, train lover, leisure-hedonic traveller, and family traveller) and characterized themaccording to personal/household characteristics, the most likely train trip by therespondent, factors travellers need or care about, do not want or do not find important(i.e., where poor service will be tolerated), and factors regarding other modes that wouldencourage train use. They argued this indicates that the intercity rail travel market has amore complex structure than the commonly-used classification into business and non-business travellers and that adapting services and policies to the different segments ofneeds and preferences would improve the effectiveness of marketing and policy.19
They distinguished travellers in three groups: strongest preference for car, i.e., alwayschoose car (37%), fairly strong preference for car (33%), and least strong preference forcar (30%). Men more often than women showed a strong preference for car, and cardependence increased with age and decreased with train experience.20 The six attitudes were: need for reliable and stress-free commute, need for privacy andcomfort, complexity of trip-making behaviour, tolerance to waiting and walking, generalattitude toward public transportation, and perceived safety of the travel environment.21 The six travel behaviour segments were: (1) malcontented motorists (30%), willing toreduce car use for altruistic motives or to avoid congestion, but held back by weakperceptions of behavioural control; (2) complacent car addicts (26%), not willing toreduce car use because they do not see the point of it; (3) die hard drivers (19%), with astrong resilience to reducing car use; (4) aspiring environmentalists (18%), with a
practical approach to car use and a high propensity to use alternatives, but constraintslimit choice; (5) car-less crusaders (4%), with a high sense of environmental awarenessand concern and a strong preference for other modes than the car; (6) reluctant riders(3%), that use alternative modes less voluntarily but because of constraints onbehaviour. Segments 1 to 4 were car owning, 5 and 6 not.
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different reasons, and have different levels of commitment to current
behaviour. Murray, Walton and Thomas (2010) investigated public
transport attitude among car drivers and found that level of prejudice to
public transport was associated with among other things use of public
transport and beliefs about public transport and the environment. Because
social norms played an important role in the prejudice among non-users,
investments in the quality of service may have little effect on their
attitudes and use. Promoting ridership, they argued, should therefore
focus more on framing public transport usage as normal. Cheng (2010)looked at passenger anxiety as a challenge for travelling by train. Delays,
transfers, crowding, access to the station and searching for the right train/
platform contributed most to anxiety, while considerable differences were
found between subgroups based on gender, age, and frequency of use.
Gatersleben & Haddad (2010) observed four stereotypes of the typical
bicyclist22 and showed how these perceptions related to bicycling
behaviour and intentions, whereas Heinen, Maat and van Wee (2011)
found three attitudinal factors related cycling to work, i.e. awareness, trip-
based benefits and safety, with different effects over various commute
distances. Gtz et al. (2003) investigated the relation between various
attitudinal, motivational and lifestyle dimensions and variability in travel
behaviour and so identified five basic mobility orientations23. Bamberg and
Schmidt (2001) used attitude toward policy measures restricting private
22 The four stereotypes were: responsible bicyclists, who use the bike safely andresponsibly; lifestyle bicyclists, who are keen on cycling and spend time and money ontheir bike; commuters, professionals who use the bike to go to work; and hippy-go-lucky,kind people who use the bike for regular non-work activities. These perceptions variedbetween bicyclist and non-bicyclists and with frequency and motivation of past cyclingbehaviour.23 The five basic mobility orientations were: (1) traditional domestics, oriented towardsfamily and security and no specific modal preference; (2) reckless car fans, orientedtowards career and achievement and with a very strong car preference; (3) status-
oriented automobilists, oriented towards prestige, with a preference for car and a strongsense of insecurity regarding other modes; (4) traditional nature lovers, oriented towardspreservation of nature, enjoy walking and have tram as favourite mode of transport; and(5) ecologically resolute, a young and technically minded group that rejects the car forecological reasons and have bicycle as favourite mode of transport.
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car use as basis for segmentation. Raney et al. (2000) discussed the
influence of a variety of non-traditional transport-related motives (i.e.,
work, family, leisure, independence, ideology) through which behavioural
reactions are filtered. Transportation research has long neglected these
motivational factors, despite the accumulating evidence of their potential
to account for heterogeneity in travel behaviour (Popuri et al. 2011;
Gardner & Abraham 2008; Cao & Mokhtarian 2005a; 2005b; Choo &
Mokhtarian 2004; Steg, Vlek & Slotegraaf 2001; Steg, Geurs & Ras 2001);
Kitamura et al. 1997); travel surveys mostly still do not ask for peoplesmotivation for travel other than trip purpose and in transport models
motivational factors are usually modelled as a part of a catch all error
term (Burnett & Hanson 1982).
Others have argued that habituation can importantly distinguish between
travellers. Much of travel behaviour is highly repetitive, with commuting
as a dominant travel pattern. Experiences with trips and travel modes arean important source for learning, enabling people to make travel choices
in a rather mindless, habitual manner for trips that have become
sufficiently familiar. Past behaviour could thus well account for differences
in travel behaviour and in sensitivity to changes in the transport system
between people, as much of the screening of alternatives has taken place
in the past (Murray, Walton & Thomas 2010; Diana & Mokhtarian 2009;
Mondschein et al. 2006; Punj & Brookes 2001; Kitamura 2000;
Verplanken et al. 1994; Salomon et al. 1993). Car dependence mostly is
associated with a travel choice set that excludes any alternative but the
car, because of mode captivity or car being the dominant best alternative,
by an objective lack of alternatives or by commitments that require a car
(Brindle 2003a; Goodwin 1995). But there is also increasing evidence
that, based on their preference for car, people develop their lifestylearound car availability, eventually making them dependent on it for most
regular and occasional trips (Brindle 2003a; Goodwin 1995). Dupuy
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(1999) distinguished three positive, accumulating effects of the
automobile system supporting car dependence for its users: the club
effect (by obtaining a drivers license), the fleet effect (by acquiring a
car), and the network effect (by using the car). This magic circle of
positive effects, Dupuy argued, makes it essential for travellers to belong
to the system and increasingly difficult for members to do without a car;
even substantial economic disincentives may then be unlikely to lead to
significant reductions in car use (Jakobsson et al. 2002). Goodwin (1995)
however pointed to the fact that although 50 to 80 percent of peopleperceive themselves to be generally dependent on car use, only between
10 and 30 percent of their trips can unambiguously be identified as both
strictly necessary and provided with no alternative, making it relevant to
distinguish between car dependent people and car dependent trips. Jekel
(2011) observed similar figures for the Netherlands, Litman (2003) and
Kenworthy (1995) discuss international comparisons of car dependence.
Hailu et al. (2005) showed that mode dependence may also relate to habit
or preference to a specific activity location. Huff and Hanson (1990) also
argued that locational persistence may account for a considerable part of
the systematic regularities in travel behaviour, with activity locations
playing a substantial role in structuring individual travel patterns and
restricting the opportunity set. This also points to travel being a derived
demand, sub-ordinate to mobility-related decisions that define a persons
travel choice set, and that inertia of travel behaviour may thus the more
relate to such prior decisions. One way or the other, studies of travel
behaviour should include measures of dependence or habituation, such as
the past and current commitments to car (driving license, ownership) and
public transport (season-ticket ownership) that tend to lock people into
inert travel patterns (Mondschein et al. 2006; Anable 2005; Simma &Axhausen 2003; 2001). Rooijers and Welles (1996), for instance,
distinguished five subgroups of travellers based on the nature and
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strength of their travel habits and the associated implications for policy24.
Whats more, they argued that habits are not only an unavoidable feature
of travel behaviour, but a functional one as well; policies can be aimed at
breaking habits that are considered to be undesirable but also at the
formation and perpetuation of habits that are considered to be desirable.25
People may thus differ in their travel preferences and experiences and the
nature and strength of their travel habits, and consequently have different
travel choice sets; i.e, people with objectively comparable characteristics
(e.g., trip purpose) and opportunity sets may have different consideration
sets. Some have argued that people are likely to have more than a single
consideration set, a behavioural repertoire consisting of different choice
sets for different choice contexts (e.g., activities, times of day, locations,
trip purposes) so that there is reason for expecting both repetition and
variability in a persons travel behaviour (Anable 2005; Mokhtarian &
Salomon 1997; Hanson & Huff 1988; Huff & Hanson 1986). Althoughmuch of transportation research still relies on travellers making reasoned
choices, the extent to which travel behaviour is reasoned or inert may
thus differ between people as well as between choice contexts for any
individual person. The next section first discusses the basic assumptions
underlying rational behaviour in mainstream economics, followed in
section 2.3 by alternative approaches proposed in behavioural economic
literature that may help advance our understanding of differences
between people in the apparent rationality of their travel behaviour.
24 Travellers with a strong and undesirable travel habit; a weak and undesirable travelhabit; hardly, if any, travel habit; a weak and desirable travel habit; a strong anddesirable travel habit. A strong and undesirable car habit can only be broken by external,restrictive push-measures making car use less feasible (e.g., banning cars from citycentre, restricting road capacity) or considerably less attractive (e.g., limiting or pricing
parking, maintaining traffic congestion). Pull-measures aimed at influencing the rationalconsideration of alternatives will only become effective after sufficient discouragementand breakdown of existing habits (see also Steg 2003).25 Habits may however only be predictive of future behaviour when circumstances remainrelatively stable (Bamberg & Schmidt 2001; Bamberg, Ajzen & Schmidt 2003).
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2.2 What is rational behaviour according to mainstreameconomics?
Mainstream economists try to explain the world by assuming that the
phenomena they observe are the outcome of rational decisions by people
maximising their individual utility (Becker 1978). The behaviour of homo
economicus is assumed to be motivated by self-interest, which is often
traced back to Epikouros. This ancient Greek philosopher stated that the
pursuit of happiness and the avoidance of pain are the first impulses of
animals and of newborn babies, and therewith a fundamental stimulus of
human behaviour (Russell 1995). Also Bentham (1879) noted: nature
has placed mankind under the governance of two sovereign masters, pain
and pleasure [] they govern us in all we do, in all we say, in all we
think. But perhaps better known, Smith (1776) stated: it is not from the
benevolence of the butcher, the brewer, or the baker, that we expect our
dinner, but from their regard to their own interest [] their self-love []their advantages. In the pursuit of his self-interest, homo economicus is
assumed to choose the best bundle of goods and services available in the
market place, consistent with his limited resources, and using utility
maximisation as the decision rule.
Bentham (1879) aligned utility with well-being, defining it as: the
property in any object [] to produce benefit, advantage, pleasure, goodor happiness or to prevent the happening of mischief, pain, evil or
unhappiness. Van Praag (1993) argued that the attitude of economics
towards the concept of utility is ambiguous and that its exact meaning
(and measurability) continue to be a matter for discussion. Two prominent
ways of interpreting utility presented in literature are hedonic welfare (or
happiness) and preference satisfaction (or desire-fulfilment) (Sen 1995;
Cohen 1993; Brouwer et al. 2008). The first considers utility as a
desirable state of happiness; Benthams definition above is an example.
The second interpretation considers utility as a way of treating how people
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make preference orderings of states of the world with their preference
being more satisfied as higher ranking states are reached; take for
instance Bouldings (1981) definition of utility: a hypothetical measure of
well-being of a person or group, particularly as expressed in their
individual preferences. Utility is that which goes up when a change
produces a situation that is preferred to the previous situation in the mind
of some evaluator. Either way, motivation for behaviour in mainstream
economics is typically consequentialist, that is, decision makers derive
utility from the outcomes of behaviour and not from the behaviour itself orthe underlying intentions (Brouwer et al. 2008). Moreover, individual
preferences are assumed to be exogenous, determined outside the
economic system; mainstream economists are primarily interested in the
bundle of goods and services a person prefers, not so much in why the
person derives most utility from any particular bundle. Preferences are
assumed not to change substantially over time, not to be very different
between wealthy and poor persons, or even between persons in different
societies and cultures (Becker 1978); one does not argue over tastes for
the same reason that one does not argue over the Rocky Mountains
both are there, will be for the next year, too, and are the same for all
men (Stigler & Becker 1977); people are presumed able to choose in
accordance with their own preferences, whatever these may be, and the
economist does not feel himself obliged to inquire deeply into the contentof these preferences (Buchanan 1987). The economists task simply is to
trace the consequences of any given set of preferences (Friedman 1962).
The choices ofhomo economicus are supposedly rational, with rationality
referring to the logic of choice. People are expected to make consistent
and transitive decisions based on utility maximisation. In order to make
this possible, individuals are assumed to have complete information of theutility providing attributes of all available alternatives and the
environment of choice, including perfect foresight, and that they are not
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hampered by any cognitive limitations and thus able to perform all
computations required to determine the optimal outcome of choice (Allais
1953; Von Neumann & Morgenstern 1953; Hogarth 1986). The
assumption of complete information does, however, not necessarily imply
that the individual knows everything; he may have to make choice under
risk. The individual then knows the set of possible consequences, but is
uncertain about the exact relation between choice and consequence.
Choice under risk now requires not only preferences among consequences,
but also the use of probability and caution factors about the relationbetween actions and consequences (Fisher 1930; Arrow 1996). Since the
days of Bernoulli, early 18th century, economic man was assumed to be
risk neutral and to choose among uncertain outcomes of choice according
to their expected utility, the utility of each outcome weighed by his
knowledge or beliefs of their probability of occurring (Von Neumann &
Morgenstern 1953; Savage 1972; Samuelson & Nordhaus 1995; Tversky
& Kahneman 1981; Allingham 1999). Choice under risk is not a wild
guess, but an informed prediction using certainty equivalents. Such
rational expectations, while not necessarily correct, supposedly are not
systematically biased (Baumol & Blinder 1999; Samuelson & Nordhaus
1995).
Considering the time it has functioned as the mainstream economic
approach to individual behaviour, despite persistent criticism for its
descriptive accuracy, homo economicus must be regarded a successful
theory of individual behaviour. Its success and influence as well as its
controversiality within and beyond economics manifest itself in the usually
rather polemic discussions between critics and advocates and in the
metaphors and anecdotes used to enforce the arguments (some of which
will be quoted below).
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Advocates
According to Becker (1978), one of the principal arguments in favour of
homo economicus as an economic theory of individual behaviour concerns
its appeal: a comprehensive one that is applicable to all human
behaviour, be it behaviour involving money prices or imputed shadow
prices, repeated or infrequent decisions, large or minor decisions,
emotional or mechanical ends, rich or poor persons, men or women,
adults or children, brilliant or stupid persons, patients or therapists,
businessmen or politicians, teachers or students. This, however, has tobe considered within the proper choice environment. Buchanan (1987)
and Williamson (1963), among others, posed that homo economicus
should be viewed as a theory of individuals who choose on markets and
that the nature of the process on markets assures proper motivation;
Markets are institutions of exchange; persons enter markets to exchange
one thing for another. They do not enter markets to further some supra-
exchange or supra-individualistic result (Buchanan 1987). Competitive
markets thus force people to be effective in following the economic
rationale. Otherwise they will be exploited and eventually withdraw;
Since only the fittest survive, we need only a theory of the fit (Cyert &
March 1963). Lucas (1986) posed to restrict the application of such a
theory to circumstances which may be considered as approximately
stationary, when people have had sufficient time and opportunity to adaptto the performance incentives operating in their choice environment.
Camerer (1999), Vlek (1990) and Thaler (1981) argued that behaviour
will be closer to the normative model, the larger the stake; but in practice,
only decisions that have a large impact get the amount of attention that
may lead to an optimal solution. The implication of narrowing the scope
obviously is that the range of phenomena to which the model can be
applied is seriously limited (Hogarth 1986).
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But perhaps more important to note, the assumptions underlying homo
economicus -more or less homogenous and stable preferences and
consistent and transitive choice using a single decision rule- were not
chosen for their descriptive accuracy, but for the purpose of analytical
convenience (Becker & Mulligan 1997). In economic analysis, realism of
the behavioural assumption is sacrificed to avoid a diversion from the
proper focus (Akerlof 1970). After all, the focus of mainstream economic
analysis typically is on the outcomes of aggregate behaviour in the
context of changes in conditions, institutions and policies (Arrow 1994;Hogarth 1986; Heiner 1983). For this purpose, individuals are assumed to
behave as if they were rational (Friedman 1962). In reality people,
however, need not necessarily be conscious of their efforts to maximise
nor be able to describe in an informative way the reasons for the
systematic patterns in their behaviour. Although people may sometimes
behave erratically, it is assumed to be of random nature. Hennipman
(1945) and Akerlof (1984), among others, have advanced the idea of
homo economicus as a useful heuristic device for generating hypotheses
to explicate empirical phenomena in areas where little data exists; rational
choice then serves as a benchmark (Handgraaf & van Raaij 2005; van
den Bergh, Ferrer-i-Carbonell & Munda 2000; Keuzekamp 1999;
Loewenstein 1992), an operational definition (Hogarth 1986), a standard
of comparison (Akerlof 1984) or a starting point for theorizing (Van Raaij1985). If we know what would happen under these hypothetical
conditions, we may better understand what does happen under actual
conditions (Fisher 1930).
All in all, Becker (1993b) posed, mainstream economists primarily
advocate homo economicus as a method of analysis, applicable to
individuals participating in market interactions under certain well-described circumstances, not as an assumption about particular
motivations of individual decision makers, who in reality may be driven by
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a much richer set of values and preferences. Economic man strives for
optimal solutions in a simplified world.
Critics
Samuelson (1937) posed that it is extremely doubtful whether we can
learn much from considering such an economic man, whose tastes remain
unchanged, who seeks to maximise some functional of consumption alone,
in a perfect world, where all things are certain and synchronised. The
prevailing dissatisfaction with homo economicus within economics26 was
clearly portrayed by Tomer (2001): Economic man is far from being a
self-actualised human, a mature fully integrated human who has realised
a significant degree of his personal potential. And economic man is still
further from being an enlightened being. Economic man, as he is
ordinarily understood, is not capable of empathy, significant intellectual or
intuitive insight, transcendental oneness or other capabilities of a
transverbal nature. Nor for that matter does economic man have personalproblems; he does not have psychological hangups or evil intentions.
Economic man, after all, is simply a machine-like version of a person who
has achieved a somewhat typical level of development in a modern
capitalistic country. The principal critiques against homo economicus
following from these quotes concern the descriptive accuracy of the
underlying assumptions of rationality and the reliance on context-free
individual utility maximisation as the single decision rule. Spiegler (2011)
argued that the mainstream approach may be a useful benchmark to
understand behaviour, but that not all observed behaviour can be
rationalized and models departing from rational behaviour assumptions
can be more useful to explain phenomena. Savage (1972) took a firmer
26 Characterizations include: rational fool (Sen 1977), pleasure machine metaphor (Thaler
1985), elegant and normatively sanguine theoretical edifice (Laibson & Zeckhauser1998), convenient fiction (Stiglitz 1989), robot-like expert (Thaler 1980), the spittingimage of a completely emotionless being such as Star Treks Mr Spock (Kaufman1999), a man with an irrationally rational passion for dispassionate calculation (Clark1918), a boys game in a sandbox (McCloskey & Murray 1996).
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position stating that the rationality assumption does not correspond even
roughly with reality; with a wink to Epikouros he noted: formal reasoning
presumably plays no role in the decisions of animals, little in those of
children, and less than might be wished in those of men. 27
Simon (1976) posed that behaviour conforms only reasonably close to
what mainstream economists consider as rational in situations that are
sufficiently simple and transparent. Understanding how people would
behave under assumptions of complete information and perfect reasoning
and motivation, however, is of limited value in all other situations, when
for instance alternatives are not clearly defined in advance and
information and computational ability are limited. In general, people do
not seem to apply a rational strategy, particularly when facing
uncertainty; tend to neglect the problem or to avoid uncertainties, leading
to bias and systematic errors (Thaler 1991; Ajzen 1977; Cyert & March
1963), and are only occasionally sufficiently involved with choicesituations to collect and consider information carefully (Van Raaij & Ye
2005). Likewise, Anderson (2000) noted: we are not very good at
judging probabilities; we do not think about risks in the way decision
theorists think we ought; we do not order our preferences consistently;
we care about sunk costs; and we systematically violate about every
logical implication of decision theory. There is probably no other
hypothesis about human behavior so thoroughly discredited on empirical
grounds that still operates as a standard working assumption in any
discipline (see also Folmer 2007). Roth (1996) accentuated that even
when market competition would provide the proper motivation for
27 In a more anecdotal style: the economists traditional picture of the economyresembles nothing so much as a Chinese restaurant with its long menu. Customerschoose from what is on the menu and are assumed always to have chosen what most
pleases them. That assumption is unrealistic, not only of the economy, but of Chineserestaurants. Most of us are unfamiliar with nine-tenths of the entrees listed; we seeminvariably to order either the wrong dishes or the same old ones. Only on occasions whenan expert does the ordering do we realize how badly we do on our own and what goodthings we miss (Scitovsky 1976).
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behaving rationally, the validity of the mainstream model can be expected
to be a property of the environment -or culture (Hofstede 2010)- as much
as of the individual.
Rationality confined to internal logic of choice makes it a rationality of
means, focussing only on how given objectives are achieved, whatever
those objectives may be (Baumol & Blinder 1999). This focus on simple
and easily characterizable motives and the disregard of the deeper and
more sacred aspects of life is insufficient and also one of the oldest and
more fundamental critiques of economic thinking (Sen 1987; Arrow 1997;
Bell 1982; Bovenberg & van de Klundert 2006; Folmer 2007). Zafirovski
(1999) posed that the utility optimisation principle is usually extended to
all human behavior and so treated as an explanatory deus ex machina of
a virtually infinite range of social economic phenomena and that some
economists show a remarkable facility or unbearable lightness in
(mis)using the utility function, by placing virtually anything in it. Spashand Biel (2002) argued that under this assumption nothing but egoism is
easily explained and altruism, habits, addiction, lexicographic preferences,
social norms, basic values and fundamental ethical beliefs are among the
list of ignored aspects of human psychology.28 Decision makers ought to
be highly detached, cool, and utterly objective when calculating the
expected utility of whatever choices they make (Janis & Mann 1977).
Tomer (2001) added that the preoccupation ofhomo economicus with his
individual utility is deficient in two ways. First, although it may be fair to
claim that people generally pursue their self-interest, it is the question to
what extent it is their main preoccupation. A second question concerns
what actually is meant by self-interest and individual utility. The self-
interest of homo economicus is often equated with independence and
28 They drew a comparison with the saying al